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More than words: Can tone of consumer product reviews help predict firms’ fundamentals?

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  • Shunyao (Cynthia) Jin

Abstract

Although financial market participants are increasingly interested in the financial value of unstructured qualitative information regarding the prospects of a firm, empirical evidence remains sparse on the properties of qualitative content in consumer product reviews and their capital market implications. Using a broad sample of consumer reviews posted on Amazon.com, I examine whether the linguistic tone of aggregate consumer product reviews conveys information that is associated with firms’ sales, earnings, stock returns and risk. I find that aggregate review tone successfully predicts a firm's forthcoming quarterly sales. Moderating analyses show that this predictability is stronger for firms operating in a highly competitive environment. I further find that review tone predicts a firm's quarterly earnings surprises, abnormal stock returns and risk. A path analysis shows that the effect of review tone on stock prices is partially channeled through its effect on firms’ earnings. I finally find that negative review tone is more informative and useful than positive tone in predicting a firm's fundamentals. Importantly, these results hold after controlling for other review characteristics, including review rating, review volumeand review dispersion. Overall, my findings highlight the importance of considering the tone of consumer reviews when evaluating a firm's prospects and value.

Suggested Citation

  • Shunyao (Cynthia) Jin, 2023. "More than words: Can tone of consumer product reviews help predict firms’ fundamentals?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 50(9-10), pages 1910-1942, October.
  • Handle: RePEc:bla:jbfnac:v:50:y:2023:i:9-10:p:1910-1942
    DOI: 10.1111/jbfa.12680
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    as
    1. David F. Larcker & Anastasia A. Zakolyukina, 2012. "Detecting Deceptive Discussions in Conference Calls," Journal of Accounting Research, Wiley Blackwell, vol. 50(2), pages 495-540, May.
    2. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    3. Paul C. Tetlock & Maytal Saar‐Tsechansky & Sofus Macskassy, 2008. "More Than Words: Quantifying Language to Measure Firms' Fundamentals," Journal of Finance, American Finance Association, vol. 63(3), pages 1437-1467, June.
    4. Mahmoud El‐Haj & Paul Rayson & Martin Walker & Steven Young & Vasiliki Simaki, 2019. "In search of meaning: Lessons, resources and next steps for computational analysis of financial discourse," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 46(3-4), pages 265-306, March.
    5. Robert Jacobson & Natalie Mizik, 2009. "The Financial Markets and Customer Satisfaction: Reexamining Possible Financial Market Mispricing of Customer Satisfaction," Marketing Science, INFORMS, vol. 28(5), pages 810-819, 09-10.
    6. Sanjiv R. Das & Mike Y. Chen, 2007. "Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web," Management Science, INFORMS, vol. 53(9), pages 1375-1388, September.
    7. Pevzner, Mikhail & Xie, Fei & Xin, Xiangang, 2015. "When firms talk, do investors listen? The role of trust in stock market reactions to corporate earnings announcements," Journal of Financial Economics, Elsevier, vol. 117(1), pages 190-223.
    8. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
    9. Huang, Jiekun, 2018. "The customer knows best: The investment value of consumer opinions," Journal of Financial Economics, Elsevier, vol. 128(1), pages 164-182.
    10. Chia-Chun Hsieh & Kai Wai Hui & Yao Zhang, 2016. "Analyst Report Readability and Stock Returns," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 43(1-2), pages 98-130, January.
    11. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    12. Tim Loughran & Bill Mcdonald, 2014. "Measuring Readability in Financial Disclosures," Journal of Finance, American Finance Association, vol. 69(4), pages 1643-1671, August.
    13. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    14. Hoberg, Gerard & Lewis, Craig, 2017. "Do fraudulent firms produce abnormal disclosure?," Journal of Corporate Finance, Elsevier, vol. 43(C), pages 58-85.
    15. Hailiang Chen & Prabuddha De & Yu (Jeffrey) Hu & Byoung-Hyoun Hwang, 2014. "Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media," The Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1367-1403.
    16. Feng Li, 2010. "The Information Content of Forward‐Looking Statements in Corporate Filings—A Naïve Bayesian Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 48(5), pages 1049-1102, December.
    17. Craig Lewis & Steven Young, 2019. "Fad or future? Automated analysis of financial text and its implications for corporate reporting," Accounting and Business Research, Taylor & Francis Journals, vol. 49(5), pages 587-615, July.
    18. Xueming Luo & Jie Zhang & Wenjing Duan, 2013. "Social Media and Firm Equity Value," Information Systems Research, INFORMS, vol. 24(1), pages 146-163, March.
    19. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    20. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    21. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    22. Xinshu Zhao & John G. Lynch & Qimei Chen, 2010. "Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(2), pages 197-206, August.
    23. Gus De Franco & Ole†Kristian Hope & Dushyantkumar Vyas & Yibin Zhou, 2015. "Analyst Report Readability," Contemporary Accounting Research, John Wiley & Sons, vol. 32(1), pages 76-104, March.
    24. Li, Xiaorong & Wang, Steven Shuye & Wang, Xue, 2019. "Trust and IPO underpricing," Journal of Corporate Finance, Elsevier, vol. 56(C), pages 224-248.
    25. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    26. Seshadri Tirunillai & Gerard J. Tellis, 2012. "Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance," Marketing Science, INFORMS, vol. 31(2), pages 198-215, March.
    27. Hang Nguyen & Roger Calantone & Ranjani Krishnan, 2020. "Influence of Social Media Emotional Word of Mouth on Institutional Investors’ Decisions and Firm Value," Management Science, INFORMS, vol. 66(2), pages 887-910, February.
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